Similarly, the panel was uncomfortable with the approach taken by previous studies to assess job openings created by turnover. Turnover rates based on net (rather than gross) flows were estimated using cross-sectional (rather than time series) data. The validity of such an estimation technique as a basis for forecasting requires that the components of these single-year rates be stable over time. No effort was made to validate this assumption.1

Having rejected the previously used models, the panel explored the feasibility of developing projections of the size and characteristics of the future workforce of biomedical and behavioral scientists employing demographic techniques through the use of a life-table model. The data upon which a life-table model is based are the known characteristics of an existing population. In this case, characteristics of interest include age, employment sector, and employment status. Changes are projected in these characteristics based on the life history of the members of the population. Rates of transition (from employed to unemployed by age group or death by age group, for example) are calculated and applied to the behavior of the population in future years. Rates of entry to the system are also an important element of the model. With these techniques, the model can be used to answer the following questions:

What will the characteristics of the labor force be in five years?

What will the retirement rate be in the near future?

How many new openings will there be if the behavior of the population in the future is the same as it was in the past?

Although life-table models can be used to obtain estimates of new openings, it is important to note that they should not be used, mechanically, to perform the task NIH set for the study committee: that is, to estimate future needs for biomedical and behavioral research scientists and the role the National Research Service Awards (NRSA) program can play in meeting those needs. The committee arrived at its recommendations through a process that involved gathering a large amount of both quantitative and qualitative information about future needs for research personnel in different fields in the biomedical and behavioral sciences. In future reports, the panel felt that life-table models could be useful in estimating an "other things equal" baseline.2

In this exploratory effort, the panel developed a life-table model using a database that could be used by NIH were it to adopt the model as an aid in formulating its policy decisions with respect to training. A primary objective of this paper is to determine whether the database is adequate to support future modeling efforts and to

1

A demographic model that employed similar estimation procedures was developed by Xie (1995) to track student commitment to science and engineering careers as they flow through the educational system.

2

The panel felt, however, that the estimation of such a baseline would be more helpful than earlier work that yielded estimates based on models that were both overly simple and reliant on strong, hidden assumptions.

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